Aminoglycoside‐mediated partial suppression of <i>MECP2</i> nonsense mutations responsible for Rett syndrome in vitro
Bibliographic record
Abstract
Rett syndrome is a pediatric neurological condition that affects primarily girls. Approximately 30% of Rett syndrome cases arise from point mutations that introduce a premature stop codon into the MECP2 gene. Several studies have now shown that certain aminoglycosides can facilitate read-through of some types of nonsense mutations in a context-dependent manner and allow the generation of a full-length protein. It remains mostly unclear whether different nonsense mutations of MECP2 will be responsive to aminoglycoside treatment. In this study, we tested whether the common premature terminating mutations of MECP2 seen in Rett syndrome cases can be partially suppressed by aminoglycoside administration. Our results show that aminoglycosides allow different mutant forms of MECP2 to be overcome in transiently transfected HEK293 cells, but with differing levels of efficiency. In addition, we also show that aminoglycosides increased the prevalence of full-length MeCP2 protein in a dose-dependent manner in a lymphocyte cell line derived from a Rett syndrome girl with the R255X mutation. This study helps to establish the "proof of principle" that some nonsense mutations causing Rett syndrome can be at least partially suppressed by drug treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".